Proceedings of the 2nd International Conference on Computer Science and Electronics Engineering (ICCSEE 2013)

Research on Underwater Polarization Image Segmentation Inspired by Biological Optic Nerve

Authors
Huibin Wang, Yurong Wu, Jie Shen, Zhe Chen
Corresponding Author
Huibin Wang
Available Online March 2013.
DOI
https://doi.org/10.2991/iccsee.2013.660How to use a DOI?
Keywords
underwater polarization image segmentation, optic nerve of mantis shrimps, feedback neural network model, parameters optimization
Abstract

Due to effects of the light by water and other particles, the quality of underwater image will degrade. The traditional underwater image segmentation methods based on intensity and spectrum have difficulty in determining boundary. Inspired by the visual system of mantis shrimps, this paper constructed a feedback neural network model, in which the parameters were optimized using machine learning method. Based on this model, we combine the polarization and intensity information to achieve the underwater polarization image segmentation. The results of experiment prove that the neural network model designed in this paper can improve the accuracy of underwater image segmentation.

Copyright
© 2013, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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Volume Title
Proceedings of the 2nd International Conference on Computer Science and Electronics Engineering (ICCSEE 2013)
Series
Advances in Intelligent Systems Research
Publication Date
March 2013
ISBN
978-90-78677-61-1
ISSN
1951-6851
DOI
https://doi.org/10.2991/iccsee.2013.660How to use a DOI?
Copyright
© 2013, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Cite this article

TY  - CONF
AU  - Huibin Wang
AU  - Yurong Wu
AU  - Jie Shen
AU  - Zhe Chen
PY  - 2013/03
DA  - 2013/03
TI  - Research on Underwater Polarization Image Segmentation Inspired by Biological Optic Nerve
BT  - Proceedings of the 2nd International Conference on Computer Science and Electronics Engineering (ICCSEE 2013)
PB  - Atlantis Press
SP  - 2646
EP  - 2650
SN  - 1951-6851
UR  - https://doi.org/10.2991/iccsee.2013.660
DO  - https://doi.org/10.2991/iccsee.2013.660
ID  - Wang2013/03
ER  -